We investigate the use of self-predicting neural networks for autonomous robot learning within noisy or partially predictable environments. A benchmark experiment is performed in ...
James B. Marshall, Neil K. Makhija, Zachary D. Rot...
We present an integrated framework for learning asymmetric boosted classifiers and online learning to address the problem of online learning asymmetric boosted classifiers, which ...
Abstract. This paper presents a methodology for automatically customizing a scenario to suit a learner’s abilities, needs, or goals. Training scenarios are often utilized to give...
Concept indexing in multimedia libraries is very useful for users searching and browsing but it is a very challenging research problem as well. Beyond the systems' implementat...
— Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the proble...